The prolific growth of cell phones and other mobile devices like iPads and other mobile communication devices, in recent years, have increased the use of these devices in daily lives of the individual users. These devices find use mainly in entertainment, commerce and financial transaction areas. In practice it has been shown that the mobile devices are mostly associated with an individual and have characteristics, properties and preferences that are unique to the individual owner of the mobile device. This linking of the individual user with specific mobile devices has created a number of opportunities to understand the individual's preferences characteristics. This preference characteristic has been used for identifying the behavior and choices of the individuals. This has also been used by advertisers to tailor ads etc. to fit an individual's preferences and influence the purchase decisions.
A user's preferences typically depend on the users behavior patterns, which are based on the users circumstances, life constraints as well as group involvements. Any changes in these characteristics will impact the preferences and activities of the user. Hence it will be advantageous to be able to understand life changes that impact the user at an early stage by changes in the identified and historically consistent behavior patterns.
It will hence be useful to have a method and system that can provide the capability to assess the change in behavior of a mobile device in use, with a reasonable probability of success through identification of changes in locations visited and group affiliation changes. It will be further useful to have a system and method capable of correlating these changes in behavior to change in life situations of the user of the mobile device. This ability for checking and verification of the changes in life situations of a user of mobile device will be very useful in predicting the preference characteristics of a user.